Characterizing Regional Methane Emissions from Natural Gas Liquid Unloading.

Area of Science:

• Environmental Science
• Chemical Engineering
• Atmospheric Science

Background:

• Methane emissions from natural gas infrastructure are a significant contributor to greenhouse gases.
• Accurate quantification of methane emissions from specific activities like liquid unloading is crucial for effective climate mitigation strategies.
• Existing estimates may not fully capture the variability and sources of these emissions.

Purpose of the Study:

• To develop a probabilistic model for quantifying methane emissions from natural gas liquid unloading activities.
• To analyze emissions across different well types and liquid-unloading systems in 18 U.S. basins for 2016.
• To compare model-derived emissions with existing regulatory data.

Main Methods:

• Developed a bottom-up probabilistic model using engineering first-principles.
• Quantified annualized throughput normalized methane emissions (TNME) for 18 U.S. basins in 2016.
• Considered six scenarios combining well types (conventional, unconventional) and unloading systems (nonplunger, manual plunger lift, automatic plunger lift).

Main Results:

• Mean TNMEs varied from 0.0093% to 0.38% across basins, indicating high variability.
• Automatic plunger-lift systems exhibited significantly higher per-well methane emissions rates.
• Model-estimated cumulative methane emissions were approximately 4.8 times higher than those reported by the 2016 Greenhouse Gas Reporting Program (GHGRP).

Conclusions:

• Super-emitters can arise naturally from process variability, not solely from malfunctions.
• Technological disaggregation, uncertainty quantification, and regionalization are vital for accurate episodic methane emissions estimation.
• Findings help reconcile discrepancies between top-down and bottom-up emission studies.